YouTube Creator Sponsorship Intelligence

Qualify YouTube creators for sponsorship outreach in one run — real engagement rates from recent uploads, how often they already run sponsored videos, which brands they've worked with, and the public business email from their channel. Paste in channel IDs, get back a scored, ranked shortlist.

What you get

One dataset record per creator:

• Channel basics: channel ID, name, country, subscriber count
• Real performance: average views and average engagement rate across their recent uploads — not a vanity subscriber number
• Sponsorship history: how many of their recent videos were sponsored, as a count and as a percentage of uploads
• Previous sponsor mentions: the titles of videos containing paid-partnership or #ad disclosures, so you can see which brands got there first
• Contact emails: public business emails published in the channel description
• Sponsorship fit score: 0–100 combining engagement, reach, sponsorship experience, and contactability
• Tier: excellent (70+), good (40+), or emerging — a ready-made shortlist filter
• Export to JSON, CSV, Excel, or Google Sheets directly from the Apify console

Use cases

• Influencer marketing — shortlist creators by real engagement instead of subscriber count
• Sponsorship outreach — get scored prospects with a public contact email already attached
• Competitive intelligence — see which creators your competitors are already sponsoring
• Agency campaign planning — qualify a long list of channels in one run and rank them by fit
• Creator CRM enrichment — refresh engagement, sponsorship rate, and tier on a schedule

How to use

1. Paste your YouTube channel IDs — one per line (the UC... ID from a channel's URL or About page)
2. Set Recent videos per creator — how many recent uploads to analyze, 1–50 (default 10)
3. Run the actor — scored creators appear in the Dataset tab

{
  "channelIds": ["UC_x5XG1OV2P6uZZ5FSM9Ttw", "UCBJycsmduvYEL83R_U4JriQ"],
  "recentVideoCount": 20
}

More recent videos means a more stable engagement average and a more reliable sponsorship rate — 20 to 30 is a good balance for active channels.

Output format

{
  "channelId": "UC_x5XG1OV2P6uZZ5FSM9Ttw",
  "name": "Example Creator",
  "country": "AU",
  "subscribers": 50000,
  "recentVideosAnalyzed": 10,
  "averageViews": 25000,
  "averageEngagementPercent": 6.4,
  "sponsoredVideoCount": 3,
  "sponsorshipRatePercent": 30,
  "previousSponsorMentions": ["My workflow", "Desk setup 2026"],
  "contactEmails": ["partnerships@example.com"],
  "sponsorshipFitScore": 78,
  "tier": "excellent"
}

FAQ

How is engagement calculated? Likes plus comments divided by views, averaged across the recent uploads analyzed — the same way media kits are sanity-checked.

How are sponsored videos detected? From disclosure language in video titles and descriptions — "sponsored", "paid partnership", "partnered with", and #ad.

Where do the contact emails come from? Public email addresses the creator published in their own channel description. Nothing private or gated is accessed.

Why does a big channel score lower than a small one? The score rewards engagement and contactability, not raw size. A 50k channel with a 6% engagement rate and a public email will outrank a 2M channel with 0.3% engagement and no contact.

Can I run it on a schedule? Yes — re-run your creator list monthly to keep engagement rates and sponsorship history current.

What is Fixture mode? A deterministic sample creator returned without calling YouTube, useful for testing an integration end to end.